基于Design-Expert的电链锯锯齿结构参数优化

为提高电链锯的锯切效率,对电链锯锯齿的齿形结构参数进行研究,以单位锯切功为电链锯锯切效率的衡量指标,通过对电链锯锯切过程的仿真研究,得出不同结构锯齿的单位锯切功。以电链锯锯齿中的外形前角、侧刃楔角和顶刃楔角等结构参数作为影响因子,采用Box-Benhnken中心组合试验方法设计多因素正交试验,使用Design-expert软件进行数据分析得出最优齿形结构参数组合。研究结果表明,所选取的齿形结构参数对单位锯切功影响程度由大到小顺序依次为外形前角、侧刃楔角、顶刃楔角,并获得最优齿形结构参数组合,外形前角为10.92°、侧刃楔角为45.7°、顶刃楔角为45.41°。

Expert Experience and Data-Driven Based Hybrid Fault Diagnosis for High-SpeedWire Rod Finishing Mills

The reliable operation of high-speed wire rod finishing mills is crucial in the steel production enterprise.As complex system-level equipment,it is difficult for high-speed wire rod finishing mills to realize fault location and real-time monitoring.To solve the above problems,an expert experience and data-driven-based hybrid fault diagnosis method for high-speed wire rod finishing mills is proposed in this paper.First,based on its mechanical structure,time and frequency domain analysis are improved in fault feature extraction.The approach of combining virtual value,peak value with kurtosis value index,is adopted in time domain analysis.Speed adjustment and side frequency analysis are proposed in frequency domain analysis to obtain accurate component characteristic frequency and its corresponding sideband.Then,according to time and frequency domain characteristics,fault location based on expert experience is proposed to get an accurate fault result.Finally,the proposed method is implemented in the equipment intelligent diagnosis system.By taking an equipment fault on site,for example,the effectiveness of the proposed method is illustrated in the system.

Expert consensus on irrigation and intracanal medication in root canal therapy

Chemical cleaning and disinfection are crucial steps for eliminating infection in root canal treatment. However, irrigant selection or irrigation procedures are far from clear. The vapor lock effect in the apical region has yet to be solved, impeding irrigation efficacy and resulting in residual infections and compromised treatment outcomes.

Practice and Thinking of Agricultural Science and Technology Experts Serving the Grassroots to Promote Rural Revitalization

Provincial agricultural research institutes are local agricultural research institutions.They are familiar with local agricultural and ru-ral conditions,and have advantages in scientific and technological achievements,technical reserves and the construction of scientific and tech-nological talent support systems.In the process of promoting the implementation of the rural revitalization strategy,all the responsibilities and obligations of the agricultural research institute are to identify the focus of scientific and technological support and talent support in rural revital-ization,and break the bottleneck and constraints of rural revitalization.By sorting out the current situation of agricultural science and technolo-gy experts serving the grassroots in the problem of talent support for rural revitalization,this paper analyzed the existing problems and put for-ward countermeasures and recommendations.

基于Design-Expert的碱激发粉煤灰建筑外墙腻子配合比优化试验研究

为了拓展工业固体废弃物粉煤灰的回收利用途径,减少对环境造成的污染,增加其在筑材料中回收利用率。在建筑外墙腻子中加入碱性激发剂(Ca(OH)_(2)、Na_(2)SiO_(3))、粉煤灰,研究碱性激发剂的激发效果。同时通过Design-Expert设计试验,分析主要组分对腻子漆膜粘结强度、吸水量的影响。结果表明:加入碱性激发剂5%,粉煤灰32.5%时,吸水量减少14%,粘结强度增加43%。乳胶粉对吸水量、粘结强度的影响非常显著(P<0.0001),其次是粉煤灰的加入量。通过加入碱性激发剂、提高乳胶粉占比,粉煤灰掺量能达到32%~65%,原配比中水泥的掺量相对减少0%~16%。

基于ANSYS和Design-Expert的农用挖掘机斗杆机构优化设计

JKW-20山地农用挖掘机斗杆机构存在设计冗余,在保证安全可靠的前提下,为解决斗杆机构材料冗余问题,实现轻量化改进,建立了农用挖掘机挖掘装置斗杆机构耦合模型,通过ANSYS软件静力学仿真及拓扑优化,确定了斗杆机构拓扑优化新结构。由于拓扑优化结构不符合实际生产要求,基于优化结果设计斗杆变量,确定优化目标函数,利用Design-Expert进行斗杆机构尺寸优化求解。由优化结果对比可知:运用Design-Expert优化后的斗杆结构相对原结构具备更轻的质量和更大的强度,该方法不仅节约了JKW-20山地农用挖掘机的生产成本,还可为类似的机构设计提供优化思路。

基于Design Expert的煤系高岭土离心增白试验

黑岱沟矿区矸石的高岭土质量分数高达70%。从煤系资源综合利用的角度出发,利用离心选矿法脱除以铁钛类为主的高密度致色杂质,提高煤系高岭土的煅烧白度。采用Design Expert进行四因素三水平的Box-Behnken正交试验设计;探究离心转速、入料速度、入料浓度和入料时间对煅烧白度及精矿产率的影响,拟合二次方程关系模型;给出煅烧白度及精矿产率与显著因素之间的响应曲面图,发现煅烧白度主要受离心转速影响,随离心转速的增加,煅烧白度先升高后降低,而精矿产率主要受入料时间影响,随入料时间的延长,精矿产率线性增加;最终结合Design Expert模拟结果,探究最佳离心增白试验条件,即离心转速为800 r/min,入料速度为8.4 L/min,入料浓度20%,入料时间100 s时,得到最佳高岭土煅烧白度(78.80%)和精矿产率(86.31%)。

International experts consensus guidelines on robotic liver resection in 2023

The robotic liver resection(RLR)has been increasingly applied in recent years and its benefits shown in some aspects owing to the technical advancement of robotic surgical system,however,controversies still exist.Based on the foundation of the previous consensus statement,this new consensus document aimed to update clinical recommendations and provide guidance to improve the outcomes of RLR clinical practice.The guideline steering group and guideline expert group were formed by 29 international experts of liver surgery and evidence-based medicine(EBM).Relevant literature was reviewed and analyzed by the evidence evaluation group.According to the WHO Handbook for Guideline Development,the Guidance Principles of Development and Amendment of the Guidelines for Clinical Diagnosis and Treatment in China 2022,a total of 14 recommendations were generated.Among them were 8 recommendations formulated by the GRADE method,and the remaining 6 recommendations were formulated based on literature review and experts’opinion due to insufficient EBM results.This international experts consensus guideline offered guidance for the safe and effective clinical practice and the research direction of RLR in future.

Prediction System for Diagnosis and Detection of Coronavirus Disease-2019(COVID-19):A Fuzzy-Soft Expert System

In early December 2019,a new virus named“2019 novel coronavirus(2019-nCoV)”appeared in Wuhan,China.The disease quickly spread worldwide,resulting in the COVID-19 pandemic.In the currentwork,we will propose a novel fuzzy softmodal(i.e.,fuzzy-soft expert system)for early detection of COVID-19.Themain construction of the fuzzy-soft expert systemconsists of five portions.The exploratory study includes sixty patients(i.e.,fortymales and twenty females)with symptoms similar to COVID-19 in(Nanjing Chest Hospital,Department of Respiratory,China).The proposed fuzzy-soft expert systemdepended on five symptoms of COVID-19(i.e.,shortness of breath,sore throat,cough,fever,and age).We will use the algorithm proposed by Kong et al.to detect these patients who may suffer from COVID-19.In this way,the present system is beneficial to help the physician decide if there is any patient who has COVID-19 or not.Finally,we present the comparison between the present system and the fuzzy expert system.

Generalized Soft Expert Set and Its Applications

The expert set theory performs an important part in making decisions. It can successfully convey the opinions of every expert since it includes several experts. In this study, generalizations and soft expert sets are combined. First, the generalized soft expert set notion is presented, then follows the definition of operation approaches and characteristics as the complement, union, intersection, AND and OR. The application of the generalized soft expert set concept to decision issues is then presented with an example. The study also introduces the idea of a generalized soft expert matrix and demonstrates how it may be used to solve decision-making issues. The most striking aspect of this paper is to present the concepts of generalized soft expert sets and generalized soft expert matrices and to apply them to the same decision-making scenario.

Expert Consensus on Prevention and Treatment of COVID-19 Infection in Patients with Lung Cancer

Corona virus disease 2019(COVID-19)infection has become a major public health issue affecting human health.The main goal of epidemic prevention and control at the current stage in China is to“protect people’s health and prevent severe cases”.Patients with lung cancer who receive antitumor therapy have low immunity,and the risk of severe illness and death once infected is much higher than healthy people,so they are vulnerable to COVID-19 infection.At present,less attention has been paid to the prevention and treatment of COVID-19 infection in patients with lung cancer in domestic guidelines and consensus.Based on the published data in China and abroad,we proposed recommendations and formed expert consensus on the vaccination of COVID-19,the use of neutralizing antibodies and small molecule antiviral drugs for patients with lung cancer,for physician’s reference.

Expert Consensus on Nutritional Support for Children with Congenital Heart Disease(2023 Edition)

The second edition of the expert consensus on pediatric nutrition was formed based on a global update of pedia-tric nutrition guidelines or consensus worldwide,the management of congenital heart disease,and the results of multi-center clinical nutrition research for congenital heart disease following thefirst Chinese consensus edition of 2016.The consensus was also shaped by the results of three discussion sessions and two questionnaires con-ducted by the 13-member collaboration group.This process was informed by both clinical guidelines and expert consensus.The quality of literature,both in English and Chinese,and the level of recommendations were evaluated using the Grading of Recommendations Assessment,Development,and Evaluations(GRADE)system.

Multi-Attribute Group Decision-Making Method under Spherical Fuzzy Bipolar Soft Expert Framework with Its Application

Spherical fuzzy soft expert set(SFSES)theory blends the perks of spherical fuzzy sets and group decision-making into a unified approach.It allows solutions to highly complicated uncertainties and ambiguities under the unbiased supervision and group decision-making of multiple experts.However,SFSES theory has some deficiencies such as the inability to interpret and portray the bipolarity of decision-parameters.This work highlights and overcomes these limitations by introducing the novel spherical fuzzy bipolar soft expert sets(SFBSESs)as a powerful hybridization of spherical fuzzy set theory with bipolar soft expert sets(BSESs).Followed by the development of certain set-theoretic operations and properties of the proposed model,important problems,including the selection of non-powered dam(NPD)sites for hydropower conversion are discussed and solved under the proposed approach.These problems mainly focus on the need for an efficient tool capable of considering the bipolarity of parameters,complicated ambiguities,and multiple opinions.Supporting the new approach by a detailed comparative analysis,it is concluded that the proposed model is more comprehensive and reliable for multi-attribute group decisionmaking(MAGDM)than the previous tools,particularly considering the bipolarity of parameters under SFSES environment.

Expert Recommendation in Community Question Answering via Heterogeneous Content Network Embedding

ExpertRecommendation(ER)aims to identify domain experts with high expertise and willingness to provide answers to questions in Community Question Answering(CQA)web services.How to model questions and users in the heterogeneous content network is critical to this task.Most traditional methods focus on modeling questions and users based on the textual content left in the community while ignoring the structural properties of heterogeneous CQA networks and always suffering from textual data sparsity issues.Recent approaches take advantage of structural proximities between nodes and attempt to fuse the textual content of nodes for modeling.However,they often fail to distinguish the nodes’personalized preferences and only consider the textual content of a part of the nodes in network embedding learning,while ignoring the semantic relevance of nodes.In this paper,we propose a novel framework that jointly considers the structural proximity relations and textual semantic relevance to model users and questions more comprehensively.Specifically,we learn topology-based embeddings through a hierarchical attentive network learning strategy,in which the proximity information and the personalized preference of nodes are encoded and preserved.Meanwhile,we utilize the node’s textual content and the text correlation between adjacent nodes to build the content-based embedding through a meta-context-aware skip-gram model.In addition,the user’s relative answer quality is incorporated to promote the ranking performance.Experimental results show that our proposed framework consistently and significantly outperforms the state-of-the-art baselines on three real-world datasets by taking the deep semantic understanding and structural feature learning together.The performance of the proposed work is analyzed in terms of MRR,P@K,and MAP and is proven to be more advanced than the existing methodologies.

Chinese expert consensus on managing thrombocytopenia in patients with cancer and liver injury

Thrombocytopenia and liver injury are serious clinical problems in patients with cancer. The etiologyof thrombocytopenia in patients with cancer and liver injury (TCLI) is complicated. Managing cancertherapy-induced thrombocytopenia has gradually become standardized, and managing liver injuryassociatedthrombocytopenia has become more effective with the approval and marketing of relevantdrugs. However, the optimal strategy for managing thrombocytopenia in patients with cancer and liverinjury remains unclear, and the superposition of thrombocytopenia and liver injury further increasesthe difficulty of cancer treatment. Therefore, the Committee of Cancer Support Therapy of the ChineseAnti-Cancer Association has organized experts to analyze and discuss relevant literature to form aChinese expert consensus on managing thrombocytopenia in patients with cancer and liver injury(2022 Edition) to guide clinical practice.

Consensus model of social network group decision-making based on trust relationship among experts and expert reliability

Due to people’s increasing dependence on social networks,it is essential to develop a consensus model considering not only their own factors but also the interaction between people.Both external trust relationship among experts and the internal reliability of experts are important factors in decision-making.This paper focuses on improving the scientificity and effectiveness of decision-making and presents a consensus model combining trust relationship among experts and expert reliability in social network group decision-making(SN-GDM).A concept named matching degree is proposed to measure expert reliability.Meanwhile,linguistic information is applied to manage the imprecise and vague information.Matching degree is expressed by a 2-tuple linguistic model,and experts’preferences are measured by a probabilistic linguistic term set(PLTS).Subsequently,a hybrid weight is explored to weigh experts’importance in a group.Then a consensus measure is introduced and a feedback mechanism is developed to produce some personalized recommendations with higher group consensus.Finally,a comparative example is provided to prove the scientificity and effectiveness of the proposed consensus model.

Fuzzy Soft Expert Matrix Theory and Its Application in Decision-Making

A unique mathematical strategy for dealing with uncertainty is fuzzy soft set theory. In this paper, we propose fuzzy soft expert matrices and describe numerous varieties of fuzzy soft expert matrices, as well as specific operations. Finally, by applying these matrices to decision-making scenarios, we widen our methodology.

复杂石墨阵列快速时变热耦合控制方法

为了在高超声速飞行器结构热试验中准确模拟真实服役热环境,用快速时变热耦合控制方法对复杂石墨阵列进行控制.采用热耦合控制方法将瞬态热损失与瞬态黑体辐射量代入控制方程,实时获取试验件的真实热响应状态;研究了结构热试验热载荷典型历程及石墨阵列控制响应特性,设计了基于结构热试验的专家PID控制策略,给出了复杂石墨阵列全历程分段控制参数;研究了石墨阵列的电特性,设计了时变限伏控制策略,提高了石墨阵列的可靠性;设计了一种多温区耦合补偿控制方法,减小了温区间的耦合干扰.结果表明:试验得到的温度曲线与理论计算曲线在快速升温段的最大误差为4.8%,平稳段的最大误差为1.4%,下降段的最大误差为2.3%;有效减小了控制系统的超调量,提高了系统响应速度;使用快速时变热耦合控制方法在某试验中对复杂石墨阵列进行控制,控制误差小于1.2%.

Chinese expert consensus on prevention and treatment of delayed nausea and vomiting(2022 Edition)

Nausea and vomiting are common adverse reactions of antitumor therapy,among which chemotherapy-induced nausea and vomiting(CINV)has been studied most intensively.Because of insufficient prevention or insufficient attention,CINV brings a series of harms to can-cer patients and even lead to the delay or termination of antitumor therapy.Delayed CINV is often underestimated because it mostly occurs outside the hospital,and patients cannot report it immediately.In recent years,the proportion of outpatient chemotherapy and day-time chemotherapy patients in China has increased year by year.Therefore,the prevention of delayed CINV is particularly important.Currently,the challenges faced by delayed CINV include the need to deeply explore its physiological and pathological mechanisms,improve its risk assessment standards,and optimize its prevention programs.However,there is still lack of practice guidelines or consensus on delayed CINV.Therefore,the Committee of Neoplastic Supportive-Care of China Anti-Cancer Association organized multidisciplinary experts in this field to formulate this consensus based on the analysis and discussion of current evidence-based medical research in combination with clinical problems that need to be solved urgently.

Leading industry experts to give keynote presentations at ITMA forums

April 2023–Two industry forums on nonwovens,and textiles and colourants will be reprised at ITMA 2023 which will be held in Milan this June.The ITMA Nonwovens Forum and ITMA Textile Colourants and Chemicals Forum will feature renowned experts who will offer insights into current challenges and share ideas on how the textile industry can achieve sustainability by leveraging innovative technologies.